Physiological Data Detection for Unexpected UI Behavior
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Solution Overview
Problem
Existing technologies fail to adequately detect unexpected user interface behaviors, such as false positives and false negatives, which can lead to suboptimal user experiences.
Innovation Solution
The use of physiological data, such as eye movements and pupil dilation, to identify unexpected user interface behaviors by determining user characteristics through sensors and machine learning models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing computer-based techniques are used to detect user interface behavior, then the system operates with standard input detection methods, but unexpected user interface behaviors such as false positives and false negatives are not adequately detected
Solution Approach 1:
The patent introduces physiological data as an intermediary indicator to detect user interface behavior. Instead of directly detecting user input through standard sensors, the system uses physiological responses (eye movements, pupil dilation, heart rate) as indirect indicators of user intent and system response accuracy, thereby improving detection reliability without significantly increasing system complexity
Solution Approach 2:
The system implements feedback by continuously monitoring physiological data and comparing it with expected physiological responses to user interface actions. When discrepancies are detected (indicating false positives or false negatives), the system can identify and correct these errors, improving overall detection accuracy through iterative feedback loops
2Measurement precision
If physiological data collection is implemented to detect unexpected user interface behavior, then detection accuracy improves, but data processing requirements and computational load increase
Solution Approach 1:
The system applies partial action by selectively analyzing physiological data only during critical time windows when user interface interactions are expected to occur. Rather than continuously processing all physiological data, the system focuses computational resources on specific time periods and physiological parameters most relevant to detecting false positives and false negatives, thereby reducing overall computational energy requirements
Solution Approach 2:
The patent changes parameters by transforming raw physiological data into simplified features and metrics that capture essential information about user responses. By converting complex physiological signals into key parameters (such as pupil dilation magnitude, eye movement velocity, heart rate variability), the system maintains high detection precision while reducing the computational complexity and energy required for data processing
Data Source
AI summary
Some implementations disclosed herein provide systems, methods, and devices that use physiological data (e.g., indicative of surprise) of a user to determine that an unexpected user interface behavior occurred. In some implementations, a device having a processor implements a method. The method obtains, via a sensor, physiological data of a user during a period of time and uses the physiological data to determine a characteristic of the user during the period of time while the user is using the electronic device. The method identifies an unexpected user interface behavior occurring prior to the period of time based on the characteristic of the user during the period of time.